SimpleEval with Examples

While simpleeval is great for basic calculators, its true power shines in production environments where you need to let users define their own logic-like setting up custom alerts, dynamic pricing discounts, or conditional triggers-without exposing your server to malicious code execution.

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1. The Core Concept: Why a Rules Engine?

Imagine you are building an e-commerce platform. You want shop owners to create custom discount rules, such as: "If the user's cart is over $100 and they are a VIP, give them a 20% discount."

Hardcoding every possible rule combination into your Python backend is impossible. Instead, you let the user save the logic as a string in the database, and you evaluate it on the fly using simpleeval.

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2. Example: The Dynamic Pricing Engine

Here is how you can use simpleeval to safely process user-defined business rules.

from simpleeval import simple_eval
from simpleeval import NameNotDefined

# 1. The data coming from your application (e.g., current checkout state)
checkout_context = {
    "cart_total": 150.00,
    "user_role": "VIP",
    "item_count": 5,
    "coupon_code": "SUMMER26"
}

# 2. Custom functions we want to allow inside the rules
def calculate_tax(amount):
    return amount * 0.08

safe_functions = {
    "tax": calculate_tax,
    "max": max,
    "min": min
}

# 3. The rules defined by the shop owner (stored as text in a database)
rules = [
    {"name": "VIP Discount", "condition": "user_role == 'VIP' and cart_total > 100", "discount": 20},
    {"name": "Bulk Buyer", "condition": "item_count >= 10", "discount": 15},
    {"name": "Tax Calculation", "condition": "True", "result": "cart_total + tax(cart_total)"}
]

# 4. Processing the rules safely
print("🛒 Processing Checkout Rules...\n")

for rule in rules:
    try:
        # Evaluate the condition string safely
        is_match = simple_eval(
            rule["condition"],
            names=checkout_context,
            functions=safe_functions
        )

        if is_match and "discount" in rule:
            print(f"✅ Rule Applied: {rule['name']} - ${rule['discount']} off!")
        elif is_match and "result" in rule:
            final_price = simple_eval(
                rule["result"],
                names=checkout_context,
                functions=safe_functions
            )
            print(f"💰 Final Price (with {rule['name']}): ${final_price:.2f}")

    except NameNotDefined as e:
        # Catches if a user writes a rule using a variable that doesn't exist
        print(f"⚠️ Error in rule '{rule['name']}': {e}")
    except Exception as e:
        print(f"❌ Invalid rule syntax in '{rule['name']}': {e}")

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3. Handling Complex Types (EvalWithCompoundTypes)

By default, simpleeval restricts access to objects and methods to prevent users from escaping the sandbox (e.g., trying to run "".__class__.__mro__... to execute system commands).

If you need users to access dictionaries, lists, or object attributes within their expressions, you can use EvalWithCompoundTypes.

from simpleeval import EvalWithCompoundTypes

# A complex nested dictionary
user_data = {
    "profile": {
        "age": 28,
        "tags": ["developer", "early_adopter"]
    }
}

evaluator = EvalWithCompoundTypes(names={"user": user_data})

# Now the string can safely navigate the dictionary and lists!
expression = "user['profile']['age'] >= 18 and 'developer' in user['profile']['tags']"

result = evaluator.eval(expression)
print(f"Is target audience? {result}") # Output: True

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4. The Python Evaluation Landscape

How does simpleeval compare to other string-evaluation methods in Python?

Method	Safety	Capabilities	Best Used For
eval()	❌ Dangerous	Runs any Python code.	Strictly internal, trusted scripts.
ast.literal_eval()	✅ Safe	Only parses data structures (dicts, lists, ints).	Converting JSON/strings to Python objects safely.
simpleeval	✅ Safe	Math, logic, variables, and custom functions.	User-defined formulas, business rules, calculators.

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5. Further Reading

• [1.1] simpleeval GitHub: Advanced Usage and Security - Read the specific limitations on recursion and execution time limits.
• [2.1] Python AST Module: Abstract Syntax Trees - If you want to understand how simpleeval breaks down user strings into safe, readable nodes.
• [3.1] Building a Rules Engine: Design Patterns for Business Rules - Explore how to structure your application to support dynamic rules effectively.